The goal of the Kinetics dataset is to help the computer vision and machine learning communities advance models for video understanding. Given this large human action classification dataset, it may be possible to learn powerful video representations that transfer to different video tasks.
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The glow of the dual monitors was the only light in Elias’s cramped apartment. It was 3:00 AM, and he was staring at a progress bar that hadn’t moved in twenty minutes. On the screen, a folder labeled sat open, its contents promising a shortcut to the high-end rhinestone and vinyl designs he couldn't yet afford.
This software acts as a productivity macro within CorelDRAW to streamline production workflows for rhinestones, vinyl, and sublimation.
film industry, known for its elaborate music and choreography. Lifestyle Staples: Cuisine and Clothing
Using unlicensed software can lead to heavy fines or legal action from The Rhinestone World (TRW), especially if the business grows and becomes more visible.
1. Possible to use ImageNet checkpoints?
We allow finetuning from public ImageNet checkpoints for the supervised track -- but a link to the specific checkpoint should be provided with each submission.
2. Possible to use optical flow?
Flow can be used as long as not trained on external datasets, except if they are synthetic.
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3. Can we train on test data without labels (e.g. transductive)?
No.
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4. Can we use semantic class label information?
Yes, for the supervised track.
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5. Will there be special tracks for methods using fewer FLOPs / small models or just RGB vs RGB+Audio in the self-supervised track?
We will ask participants to provide the total number of model parameters and the modalities used and plan to create special mentions for those doing well in each setting, but not specific tracks.